Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A computing system comprising: one or more processor circuits configured to execute instruction sets of an application; a memory unit that stores at least a first knowledge cell including a first one or more object representations correlated with a first one or more instruction sets for operating a first avatar of the application and a second knowledge cell including a second one or more object representations correlated with a second one or more instruction sets for operating the first avatar of the application, wherein the first one or more object representations represent a first one or more objects of the application and the second one or more object representations represent a second one or more objects of the application, and wherein at least a portion of the first knowledge cell and at least a portion of the second knowledge cell are learned in an automatic learning process while the first avatar of the application is at least partially operated by a user; and an artificial intelligence unit that: generates a third one or more object representations, wherein the third one or more object representations represent a third one or more objects of the application; determines the first one or more instruction sets for operating the first avatar of the application based on at least partial match between the third one or more object representations and the first one or more object representations; and in response to the determines of the artificial intelligence unit, causes the first avatar of the application or a second avatar of the application to autonomously perform one or more operations defined by the first one or more instruction sets for operating the first avatar of the application at least by causing the one or more processor circuits to execute the first one or more instruction sets for operating the first avatar of the application, wherein the one or more operations defined by the first one or more instruction sets for operating the first avatar of the application correspond to the user's methodology of operating the first avatar of the application learned in the automatic learning process.
The computing system operates in the domain of artificial intelligence and avatar control within applications, addressing the challenge of enabling autonomous avatar operations based on learned user behavior. The system includes processor circuits executing application instruction sets, a memory unit storing knowledge cells, and an artificial intelligence unit. Knowledge cells contain object representations correlated with instruction sets for operating an avatar. The first knowledge cell includes object representations and instruction sets for a first set of objects, while the second knowledge cell includes representations and instruction sets for a second set of objects. These knowledge cells are partially learned through an automatic learning process while a user operates the avatar. The artificial intelligence unit generates new object representations, matches them with existing representations in the knowledge cells, and determines corresponding instruction sets. Based on this matching, the system autonomously executes operations defined by the instruction sets, replicating the user's learned methodology. The system can operate either the original avatar or a second avatar, ensuring consistent behavior based on the learned patterns. This approach enables avatars to perform tasks autonomously while adhering to user-defined methodologies, improving efficiency and reducing manual intervention.
2. The system of claim 1 , wherein the automatic learning process includes obtaining the first one or more instruction sets for operating the first avatar of the application and the second one or more instruction sets for operating the first avatar of the application using at least a tracing of the first avatar of the application.
The system relates to automated learning for operating avatars in applications, particularly in virtual environments or simulations. The core problem addressed is the manual effort required to program or control avatars, which is time-consuming and lacks adaptability. The invention automates this process by using machine learning to generate instruction sets for avatar operations. The system includes a learning module that traces the behavior of a first avatar in an application to capture its operational patterns. This tracing involves recording the avatar's actions, movements, and interactions within the application. The learning module then processes this traced data to derive one or more instruction sets that define how the avatar operates. These instruction sets are used to replicate or modify the avatar's behavior automatically. The system also includes a second set of instruction sets, which may be derived from the same tracing process or additional data sources. These instruction sets can be used to refine or enhance the avatar's operations, ensuring adaptability to different scenarios or user preferences. The automatic learning process reduces the need for manual programming, making avatar control more efficient and scalable. The system is particularly useful in applications requiring dynamic avatar interactions, such as gaming, virtual training, or simulation environments.
3. The system of claim 1 , wherein the automatic learning process includes obtaining the first one or more instruction sets for operating the first avatar of the application and the second one or more instruction sets for operating the first avatar of the application using at least a tracing of the application.
This invention relates to a system for automatically learning and generating instruction sets for operating avatars in an application, particularly in virtual or augmented reality environments. The system addresses the challenge of manually programming avatar behaviors, which is time-consuming and requires specialized expertise. By automating the learning process, the system enables developers to efficiently create and customize avatar interactions. The system obtains instruction sets for operating an avatar by tracing the application's execution. This involves monitoring and recording the application's behavior, including how the avatar responds to user inputs, environmental changes, or other triggers. The tracing process captures the sequence of operations, parameters, and conditions that govern the avatar's actions. The system then analyzes this traced data to derive one or more instruction sets that define how the avatar should operate under different scenarios. These instruction sets can be used to replicate or modify the avatar's behavior in the application. The system supports multiple instruction sets for the same avatar, allowing for different behaviors based on context, user preferences, or application requirements. The automatic learning process ensures that the instruction sets are dynamically generated and updated, adapting to changes in the application or user interactions. This approach reduces the need for manual scripting and enables more flexible and responsive avatar behaviors in interactive applications.
4. The system of claim 1 , wherein the causing the one or more processor circuits to execute the first one or more instruction sets for operating the first avatar of the application includes instrumenting the first avatar of the application or the second avatar of the application with the first one or more instruction sets for operating the first avatar of the application.
This invention relates to a system for managing avatars in an application, addressing the challenge of efficiently executing instruction sets to control avatar behavior. The system includes a processor circuit configured to execute instruction sets for operating multiple avatars within an application. The system causes the processor to execute a first set of instructions for operating a first avatar, where this execution involves instrumenting either the first avatar or a second avatar with the first instruction set. Instrumentation refers to embedding or integrating the instruction set into the avatar's operational framework, enabling the processor to control the avatar's actions, movements, or interactions within the application. The system may also include a second set of instructions for operating the second avatar, which may be executed independently or in conjunction with the first set. The instrumentation process ensures that the avatars can be dynamically controlled, allowing for real-time adjustments and interactions within the application environment. This approach enhances avatar responsiveness and adaptability, improving user experience in applications where avatars play a central role, such as virtual reality, gaming, or simulation environments.
5. The system of claim 1 , wherein the causing the one or more processor circuits to execute the first one or more instruction sets for operating the first avatar of the application includes instrumenting the application with the first one or more instruction sets for operating the first avatar of the application.
This invention relates to systems for operating avatars within an application, particularly focusing on the integration of instruction sets to control avatar behavior. The problem addressed involves efficiently managing and executing multiple instruction sets to operate different avatars in a coordinated manner, ensuring smooth and responsive interactions within the application. The system includes one or more processor circuits configured to execute instruction sets for operating avatars. Specifically, the system instruments the application with a first set of instructions to control a first avatar. Instrumentation involves embedding or integrating these instructions into the application's codebase or runtime environment to enable the avatar's operations. This may include defining movement, animations, interactions, or other behaviors of the avatar based on the instruction set. The system may also manage additional instruction sets for other avatars, allowing multiple avatars to operate simultaneously within the application. The instrumentation process ensures that the instruction sets are properly executed, enabling the avatars to perform their intended functions without disrupting the application's performance. This approach enhances the flexibility and scalability of avatar operations within the application, supporting complex interactions and dynamic behaviors.
6. The system of claim 1 , wherein the determines the first one or more instruction sets for operating the first avatar of the application based on at least partial match between the third one or more object representations and the first one or more object representations includes determining that a number of at least partially matching portions of the third one or more object representations and portions of the first one or more object representations exceeds a threshold number.
This invention relates to a system for operating avatars in an application, particularly focusing on determining instruction sets for avatar behavior based on object recognition. The system addresses the challenge of enabling avatars to interact with objects in a virtual environment by dynamically generating appropriate actions or behaviors. The core functionality involves comparing object representations detected in the environment with predefined object representations associated with the avatar. When a partial match is found, the system evaluates whether the number of matching portions between the detected objects and the predefined objects exceeds a predefined threshold. If the threshold is met, the system selects one or more instruction sets to control the avatar's actions, ensuring contextually relevant interactions. This approach enhances avatar responsiveness and realism by adapting behaviors based on environmental object recognition, improving user engagement in virtual applications. The system may also incorporate additional features from dependent claims, such as refining matches using spatial or temporal data, or adjusting thresholds dynamically based on environmental complexity. The invention is applicable in virtual reality, gaming, and interactive simulations where avatar-object interactions are critical.
7. The system of claim 1 , wherein the first knowledge cell includes a first unit of knowledge of how the user at least partially operated the first avatar of the application in a first circumstance represented at least in part by the first one or more object representations, and the second knowledge cell includes a second unit of knowledge of how the user at least partially operated the first avatar of the application in a second circumstance represented at least in part by the second one or more object representations.
This invention relates to a system for capturing and utilizing user behavior data in an interactive application, particularly involving avatars and virtual environments. The system addresses the challenge of adapting to user actions in dynamic scenarios by storing and retrieving contextual knowledge about how a user operates an avatar in different circumstances. The system includes multiple knowledge cells, each storing a unit of knowledge about user behavior. A first knowledge cell records how a user operates an avatar in a first scenario, where the scenario is defined by one or more virtual objects or environmental conditions. Similarly, a second knowledge cell captures how the same user operates the avatar in a second, distinct scenario, defined by a different set of objects or conditions. The system differentiates between these scenarios to provide context-aware responses or adaptations, improving the application's ability to assist or interact with the user based on past behavior in similar situations. This approach enables personalized and situation-specific avatar control, enhancing user experience by leveraging learned behavior patterns in varying virtual environments. The system dynamically associates user actions with specific contextual factors, allowing for more accurate predictions or automated responses in future interactions.
8. The system of claim 1 , wherein the first one or more object representations include a first stream of one or more object representations, the second one or more object representations include a second stream of one or more object representations, and the third one or more object representations include a third stream of one or more object representations.
The invention relates to a system for processing multiple streams of object representations, such as those generated in augmented reality (AR) or virtual reality (VR) environments. The system addresses the challenge of efficiently managing and integrating multiple data streams representing objects in real-time applications, where latency and synchronization are critical. The system includes a processing unit that receives and processes at least three distinct streams of object representations. Each stream contains one or more object representations, which may include 3D models, textures, or other digital assets used in AR/VR applications. The processing unit is configured to handle these streams independently or in combination, allowing for dynamic adjustments based on user interactions or environmental changes. The system may also include input interfaces for capturing real-world data, such as camera feeds or sensor inputs, and output interfaces for rendering the processed object representations in a cohesive manner. By managing multiple streams, the system ensures smooth integration of virtual and real-world elements, enhancing the user experience in immersive environments. The invention improves upon prior systems by providing a scalable and flexible architecture for handling diverse object representations in real-time.
9. The system of claim 1 , wherein at least one object of the application of the first one or more objects of the application and at least one object of the application of the third one or more objects of the application are the same.
This invention relates to a system for managing objects within an application, addressing the challenge of efficiently handling and tracking multiple objects to improve performance and reduce redundancy. The system includes a first set of objects, a second set of objects, and a third set of objects, where the second set is derived from the first set and the third set is derived from the second set. The system ensures that at least one object from the first set and at least one object from the third set are identical, allowing for consistent object references across different stages of processing. This shared object structure minimizes duplication, enhances data integrity, and streamlines operations by maintaining a direct relationship between objects in different sets. The system may be used in software applications where object tracking, versioning, or state management is critical, such as in development environments, databases, or collaborative tools. By reusing objects across multiple stages, the system reduces computational overhead and improves efficiency in object-based workflows.
10. The system of claim 1 , wherein the first one or more objects of the application do not extend one or more physical objects, the second one or more objects of the application do not extend one or more physical objects, and the third one or more objects of the application do not extend one or more physical objects.
This invention relates to a system for managing virtual objects in an application, particularly where these objects do not correspond to or extend physical objects in the real world. The system involves at least three distinct sets of virtual objects within the application, each set being independent of physical objects. The first set of virtual objects does not represent or extend any physical objects, meaning they exist purely in the digital environment. Similarly, the second and third sets of virtual objects are also entirely virtual, with no physical counterparts. This design allows for a fully digital interaction framework where all objects are abstracted from the physical world, enabling unique applications in virtual reality, gaming, or simulation environments. The system may include additional features such as user interaction mechanisms, object behavior rules, or dynamic generation of virtual objects, all operating within a purely digital context. The absence of physical extensions ensures that the system remains flexible and adaptable to various virtual scenarios without real-world constraints. This approach is useful in scenarios where digital-only interactions are required, such as in augmented reality overlays, virtual training simulations, or purely digital gaming environments.
11. The system of claim 1 , wherein the determines the first one or more instruction sets for operating the first avatar of the application based on at least partial match between the third one or more object representations and the first one or more object representations includes determining that a percentage of at least partially matching portions of the third one or more object representations and portions of the first one or more object representations exceeds a threshold percentage.
This invention relates to a system for operating avatars in an application, particularly focusing on determining instruction sets for avatar behavior based on object recognition and matching. The system addresses the challenge of enabling avatars to interact with objects in a virtual environment by analyzing visual or spatial representations of those objects. The system compares object representations from a current scene (third object representations) with predefined object representations (first object representations) associated with the avatar's behavior. When a partial match is detected, the system evaluates the degree of similarity by calculating the percentage of matching portions between the compared representations. If this percentage exceeds a predefined threshold, the system selects the corresponding instruction sets to control the avatar's actions. This approach allows the avatar to dynamically respond to objects in its environment, even when exact matches are not present, by leveraging partial similarities to trigger appropriate behaviors. The system enhances avatar interactivity by enabling flexible, context-aware responses to objects in virtual environments.
12. The system of claim 1 , further comprising: an acquisition interface that attaches the artificial intelligence unit to the first avatar of the application to obtain: the first one or more instruction sets for operating the first avatar of the application and the second one or more instruction sets for operating the first avatar of the application.
The system involves an artificial intelligence (AI) unit integrated with an avatar in a digital application, such as a virtual environment or game. The AI unit is designed to control the avatar's actions and behaviors by processing instruction sets. The system includes an acquisition interface that connects the AI unit to the avatar, enabling it to retrieve two distinct sets of instructions. The first set of instructions governs the avatar's basic operations, such as movement, interactions, and responses to user inputs. The second set of instructions modifies or enhances the avatar's behavior, allowing for dynamic adjustments based on real-time conditions, user preferences, or external data inputs. This dual-instruction approach enables the AI unit to adapt the avatar's actions more flexibly, improving responsiveness and personalization. The system may be used in applications requiring intelligent, autonomous avatars, such as virtual assistants, gaming characters, or interactive simulations. The acquisition interface ensures seamless communication between the AI unit and the avatar, facilitating real-time updates and adjustments to the avatar's behavior. This enhances the avatar's ability to perform tasks autonomously while remaining responsive to user needs and environmental changes.
13. The system of claim 1 , wherein the automatic learning process includes determining the first one or more objects of the application within a threshold distance from the first avatar of the application.
This invention relates to a system for automatically learning and managing interactions within a virtual environment, such as a video game or simulation. The system addresses the challenge of dynamically identifying and prioritizing relevant objects or entities in proximity to a user-controlled avatar to enhance immersion and responsiveness. The core system includes a learning module that processes data from the virtual environment to identify key objects or interactions that are within a defined threshold distance of the avatar. This proximity-based detection allows the system to focus computational resources on the most relevant elements, improving performance and user experience. The learning process may involve real-time analysis of spatial relationships, object attributes, and user behavior to refine the selection of objects. By dynamically adjusting the threshold distance or criteria, the system adapts to different scenarios, ensuring that the most critical interactions are prioritized. This approach optimizes resource allocation and enhances the realism of the virtual environment by ensuring that the avatar's immediate surroundings are accurately and efficiently processed. The system may also integrate with other modules to trigger actions, provide feedback, or adjust environmental parameters based on the detected objects.
14. The system of claim 1 , wherein the automatic learning process includes: determining that the first one or more instruction sets for operating the first avatar of the application temporally correspond to the first one or more object representations; and determining that the second one or more instruction sets for operating the first avatar of the application temporally correspond to the second one or more object representations.
This invention relates to a system for automatically learning associations between avatar instructions and object representations in a digital application, such as a game or virtual environment. The problem addressed is the need to dynamically adapt avatar behavior based on interactions with objects in the environment without requiring manual programming or extensive user input. The system includes a learning module that processes instruction sets for operating an avatar and object representations within the application. The learning process involves determining temporal correspondence between specific instruction sets and object representations. For example, if an avatar performs a set of actions (e.g., moving, interacting) while certain objects are present, the system identifies and records this relationship. This allows the avatar to learn and replicate behaviors associated with specific objects over time, improving responsiveness and realism in the application. The system may also distinguish between different sets of instructions and object representations, enabling context-aware behavior. For instance, the avatar could learn separate actions for interacting with a first set of objects (e.g., tools) versus a second set (e.g., obstacles). The learned associations can be used to automate avatar responses, enhance user experience, or train AI-driven characters in dynamic environments. The invention aims to reduce development effort by automating behavior mapping between avatars and objects.
15. The system of claim 1 , wherein the memory unit further stores at least a knowledge structure that includes the first knowledge cell and the second knowledge cell, and wherein the automatic learning process includes: generating the first knowledge cell of the knowledge structure; generating the second knowledge cell of the knowledge structure; and coupling the first knowledge cell of the knowledge structure to the second knowledge cell of the knowledge structure.
The system relates to an automatic learning process for generating and linking knowledge structures in a memory unit. The system addresses the challenge of organizing and connecting discrete pieces of information to form a coherent knowledge base. The memory unit stores a knowledge structure comprising at least two knowledge cells, which are generated through an automatic learning process. The first knowledge cell and the second knowledge cell are created independently and then coupled together to form a structured relationship. This coupling enables the system to establish connections between different pieces of knowledge, facilitating more efficient retrieval and reasoning. The automatic learning process dynamically builds and links these knowledge cells, allowing the system to adapt and expand its knowledge base over time. This approach improves information organization, enhances data accessibility, and supports advanced reasoning capabilities by enabling the system to recognize and utilize relationships between different knowledge elements. The system is particularly useful in applications requiring structured knowledge representation, such as artificial intelligence, expert systems, and cognitive computing.
16. The system of claim 1 , wherein the first one or more object representations are comparative one or more object representations whose at least one portion are compared with at least one portion of one or more object representations subsequent to the first one or more object representations.
This invention relates to a system for analyzing and comparing object representations, such as images or data models, to identify differences or similarities between them. The system addresses the challenge of efficiently detecting changes or correlations in sequential object representations, which is useful in applications like surveillance, quality control, or medical imaging. The system includes a processing module that generates comparative object representations, where at least one portion of these representations is compared with corresponding portions of subsequent object representations. This comparison allows the system to track variations over time or across different instances. The processing module may use techniques such as pattern recognition, feature extraction, or machine learning to perform these comparisons. The system may also include a storage module to retain the object representations and their comparative data for further analysis. The comparative analysis can be applied to various types of object representations, including images, 3D models, or sensor data. The system may highlight differences or similarities between the compared portions, enabling users to identify trends, anomalies, or specific changes. This functionality is particularly valuable in scenarios where monitoring small or incremental changes is critical, such as in industrial inspections or medical diagnostics. The system may also include user interfaces or output modules to display the comparison results in a meaningful way, such as annotated images or statistical reports.
17. The system of claim 1 , wherein the third one or more object representations are anticipatory one or more object representations whose at least one portion are compared with at least one portion of one or more object representations prior to the third one or more object representations.
This invention relates to a system for processing object representations, particularly in scenarios where anticipatory object representations are compared with prior object representations to improve accuracy or efficiency. The system includes a mechanism for generating or receiving object representations, which may be visual, textual, or other forms of data. The key feature is the use of anticipatory object representations, which are compared with at least one portion of one or more earlier object representations before the anticipatory representations are fully processed or utilized. This comparison may involve matching, alignment, or other forms of analysis to detect similarities, differences, or patterns. The system may be used in applications such as predictive modeling, real-time object tracking, or data validation, where anticipatory processing helps reduce latency or improve decision-making. The comparison process may involve machine learning, statistical analysis, or rule-based methods to determine how the anticipatory representations relate to prior data. The system may also include feedback mechanisms to refine future anticipatory representations based on the comparison results. This approach enhances the system's ability to handle dynamic or time-sensitive data by leveraging prior information to inform anticipatory processing.
18. The system of claim 1 , wherein the first knowledge cell includes at least a first portion of the user's methodology of operating the first avatar of the application in a first circumstance represented at least in part by the first one or more object representations, and the second knowledge cell includes at least a second portion of the user's methodology of operating the first avatar of the application in a second circumstance represented at least in part by the second one or more object representations.
A system for managing user methodologies in an application involving avatars and object representations. The system captures and stores distinct portions of a user's methodology for operating an avatar in different circumstances. Each circumstance is defined by one or more object representations within the application. The system includes at least two knowledge cells, where the first knowledge cell stores a portion of the user's methodology for operating the avatar in a first circumstance, and the second knowledge cell stores a portion of the user's methodology for operating the avatar in a second circumstance. The methodologies may involve actions, behaviors, or decision-making processes specific to each circumstance. The system allows for the retrieval and application of these methodologies to enhance the avatar's performance or adaptability in similar situations. The object representations may include virtual objects, environmental elements, or interactive items within the application that influence the avatar's behavior. The system may be used in gaming, virtual reality, or other interactive applications where user behavior with avatars is context-dependent.
19. A non-transitory computer storage medium having a computer program stored thereon, the computer program including instructions that when executed by one or more processor circuits cause the one or more processor circuits to perform operations comprising: accessing a memory unit that stores at least a first knowledge cell including a first one or more object representations correlated with a first one or more instruction sets for operating a first avatar of an application and a second knowledge cell including a second one or more object representations correlated with a second one or more instruction sets for operating the first avatar of the application, wherein the first one or more object representations represent a first one or more objects of the application and the second one or more object representations represent a second one or more objects of the application, and wherein at least a portion of the first knowledge cell and at least a portion of the second knowledge cell are learned in an automatic learning process while the first avatar of the application is at least partially operated by a user; generating a third one or more object representations, wherein the third one or more object representations represent a third one or more objects of the application; determining the first one or more instruction sets for operating the first avatar of the application based on at least partial match between the third one or more object representations and the first one or more object representations; and in response to the determining, causing the first avatar of the application or a second avatar of the application to autonomously perform one or more operations defined by the first one or more instruction sets for operating the first avatar of the application at least by causing the one or more processor circuits or another one or more processor circuits to execute the first one or more instruction sets for operating the first avatar of the application, wherein the one or more operations defined by the first one or more instruction sets for operating the first avatar of the application correspond to the user's methodology of operating the first avatar of the application learned in the automatic learning process.
This invention relates to a system for autonomously operating avatars in an application by learning and replicating user behavior. The problem addressed is the need for avatars to perform tasks independently while adapting to user preferences and methodologies. The system stores knowledge cells in memory, each containing object representations correlated with instruction sets for operating an avatar. These knowledge cells are learned automatically as the user interacts with the avatar, capturing the user's methodology. The system generates new object representations during operation and matches them against stored representations to determine the appropriate instruction sets. Based on this matching, the system autonomously executes the learned instructions to perform operations, either through the original avatar or a different one. This allows the system to replicate the user's learned behavior in various scenarios, improving avatar autonomy and adaptability. The automatic learning process ensures the system continuously updates its knowledge cells to refine avatar operations over time.
20. A method comprising: (a) accessing a memory unit that stores at least a first knowledge cell including a first one or more object representations correlated with a first one or more instruction sets for operating a first avatar of an application and a second knowledge cell including a second one or more object representations correlated with a second one or more instruction sets for operating the first avatar of the application, wherein the first one or more object representations represent a first one or more objects of the application and the second one or more object representations represent a second one or more objects of the application, and wherein at least a portion of the first knowledge cell and at least a portion of the second knowledge cell are learned in an automatic learning process while the first avatar of the application is at least partially operated by a user, the accessing of (a) performed by one or more processor circuits; (b) generating a third one or more object representations, wherein the third one or more object representations represent a third one or more objects of the application, the generating of (b) performed by the one or more processor circuits; (c) determining the first one or more instruction sets for operating the first avatar of the application based on at least partial match between the third one or more object representations and the first one or more object representations, the determining of (c) performed by the one or more processor circuits; (d) executing the first one or more instruction sets for operating the first avatar of the application, the executing of (d) performed by the one or more processor circuits or by another one or more processor circuits in response to the determining of (c); and (e) performing, by the first avatar of the application or by a second avatar of the application, one or more operations defined by the first one or more instruction sets for operating the first avatar of the application, wherein the one or more operations defined by the first one or more instruction sets for operating the first avatar of the application correspond to the user's methodology of operating the first avatar of the application learned in the automatic learning process.
This invention relates to a system for operating avatars in an application through learned behavior patterns. The technology addresses the challenge of enabling avatars to perform tasks autonomously by mimicking user behavior, reducing the need for manual control. The method involves accessing a memory unit containing knowledge cells, where each cell stores object representations and corresponding instruction sets for operating an avatar. These knowledge cells are partially learned through an automatic learning process while a user operates the avatar, capturing the user's methodology. The system generates new object representations, compares them to stored representations, and determines the appropriate instruction sets based on partial matches. These instructions are then executed to perform operations corresponding to the learned user behavior. The system can operate either the original avatar or a second avatar, allowing for autonomous or collaborative task execution. This approach enables avatars to adapt to user preferences and perform tasks with minimal manual intervention, improving efficiency in applications requiring avatar interaction.
Unknown
September 3, 2019
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